Lurasidone and risk for metabolic syndrome: results from short- and long-term clinical studies in patients with schizophrenia

Objective To assess the effects of treatment with lurasidone on risk for metabolic syndrome (MetS) in patients with schizophrenia. Methods Rates of metabolic syndrome during treatment with lurasidone (40-160 mg/d) were analyzed using pooled, short-term data from three randomized, double-blind, placebo-controlled studies (vs olanzapine and quetiapine XR); long-term data from two active-comparator-controlled studies (vs risperidone and quetiapine XR); and data from two open-label studies in which patients were switched from olanzapine or risperidone to lurasidone. Results MetS was defined based on the National Cholesterol Education Program criteria. In short-term studies, the odds of meeting criteria for MetS at week 6 LOCF (adjusted for baseline metabolic syndrome status) was similar for the lurasidone and placebo groups (OR = 1.18; [95% CI, 0.81-1.71]; P = .39), but the odds (vs placebo) were significantly greater for olanzapine (OR = 2.81; [95% CI, 1.53-5.15]; P < .001) and quetiapine (OR = 3.49; [95% CI, 1.93-6.29]; P < .0001). No dose effect was observed for lurasidone across the dose range of 40-160 mg/d. In long-term studies, the odds of MetS after 12 months of treatment was significantly higher for risperidone compared with lurasidone (OR = 2.12; 95% CI, 1.15-3.90; P = .016) and for quetiapine XR compared with lurasidone (OR = 3.92; 95% CI, 1.15-13.40; P = .029). In open-label extension studies, the rate of MetS decreased in patients switched to lurasidone after 6 weeks of treatment with olanzapine or 12 months of treatment with risperidone. Conclusion In this analysis of lurasidone clinical trials, the odds of developing metabolic syndrome were minimal during short- and long-term treatment with lurasidone (40-160 mg/d).

M48. IS METABOLIC SYNDROME RELATED TO COGNITIVE PERFORMANCE IN PATIENTS WITH SCHIZOPHRENIA? RESULTS FROM A DOUBLE-BLIND, ACTIVE-CONTROLLED, LURASIDONE STUDY

Background Schizophrenia is associated with cognitive dysfunction as well as cardiovascular disease (CVD). A central risk factor for CVD is the metabolic syndrome (MetS), which is of special concern in schizophrenia. The prevalence of MetS in U.S. patients with schizophrenia is higher versus general population (32.5% versus 23%). The prevalence of MetS and diabetes mellitus (DM) in those with schizophrenia double that of the general population. Adverse events of some antipsychotics used to treat schizophrenia include weight gain, obesity and other MetS complications, particularly abnormal glucose and lipid metabolism. Patients with schizophrenia have low rates of treatment for MetS and its components. Furthermore, components of MetS are risk factors for cognitive impairment and dementia in the general population. Cognitive impairment is a hallmark feature of schizophrenia, and the level of community functioning is strongly correlated with the degree of cognitive impairment. Given the importance of cognitive impairment in schizophrenia, the potential role of MetS in contributing to cognitive dysfunction is important. The objective of this post-hoc analysis was to examine cross-sectional relationships between metabolic syndrome and cognitive performance in patients with schizophrenia treated with lurasidone or quetiapine XR for 6-weeks. Methods This post hoc analysis utilized data from 6-week, double-blind, placebo-controlled trial of patients with an acute exacerbation of schizophrenia who were randomized to fixed, once-daily oral doses of lurasidone 80 mg (LUR 80 n=125), lurasidone 160 mg (LUR 160, n=121), quetiapine XR 600 mg (QXR, n=120) and placebo (PBO, n=122). Patients with metabolic syndrome (MetS) at baseline were identified based on the National Cholesterol Education Program – Adult Treatment Panel III criteria (NCEP-ATP-III). Cognitive performance and functional capacity were assessed by the CogState computerized cognitive battery at baseline and 6 weeks. Results In the acute 6-week period, LUR160 was significantly superior on the cognitive composite score to PBO (p&lt;0.05, d=0.37), while LUR 80 and QXR did not separate from PBO in the evaluable analysis sample (excluding subjects with non-evaluable composite Z-scores; n=267). A total of 45/267 (16.9%) patients met criteria for MetS. Treatment of patients with MetS group with LUR 160 (vs placebo) was associated with significantly greater week 6 improvement in the cognitive composite score (p&lt;0.05, d=1.15), while LUR 80 and QXR did not separate from PBO. In the group without MetS, LUR dose groups and QXR did not differ from PBO in the CogState composite score. In the analysis of cognitive domain scores, LUR 80 was significantly superior to PBO on working memory in the group with MetS (p&lt;0.05, d=1.01) and reasoning/problem solving in the group without MetS (p&lt;0.05, d=0.46). LUR 160 was significantly superior to PBO on processing speed in the group with MetS (p&lt;0.05, d=1.20), reasoning/problem solving (p&lt;0.05, d=0.45) and social cognition (p&lt;0.05, d=0.46) in the group without MetS. QXR was significantly superior to PBO on verbal learning and reasoning/problem solving in the group without MetS (p&lt;0.05, d=0.38 and p&lt;0.05, d=0.37, respectively). Discussion Patients with MetS responded to treatment with lurasidone with significantly improved CogState composite and domain scores. No improvement on cognition was seen in patients with MetS treated with QXR. Evaluation of potential for MetS and improvements in cognition should be important elements in the algorithm of optimization of treatment in patients with schizophrenia.

Post hoc analysis of a randomised, placebo-controlled, active-reference 6-week study of brexpiprazole in acute schizophrenia

Objective:We provide a closer look at the result of a randomised, placebo-controlled, active-reference (quetiapine XR), flexible-dose, 6-week study of brexpiprazole in schizophrenia, which did not meet its primary endpoint – change from baseline in Positive and Negative Syndrome Scale (PANSS) total score. We also investigate potential expectancy bias from the well-known side-effect profile of the active reference that could have affected the study outcome.Methods:Pre-specified sensitivity analyses of the primary end point were performed using analysis of covariance (ANCOVA) last observation carried forward (LOCF) and observed cases (OC). Post hoc analyses of change from baseline in PANSS total score were performed using the mixed model for repeated measures approach with treatment groups split by having typical adverse events with potential for functional unblinding, for example, somnolence, increase in weight, dizziness, dry mouth and sedation.Results:Pre-specified sensitivity analyses showed separation from placebo for brexpiprazole at week 6: LOCF, ANCOVA: −4.3 [95% CI (−8.0, −0.5), p = 0.0254]. OC, ANCOVA: −3.9 [95% CI (−7.3, −0.5), p = 0.0260]. Patients treated with brexpiprazole experiencing typical adverse events with potential for functional unblinding before or at Week 2 had a least square (LS) mean PANSS change of −29.5 (improvement), with a difference in change from baseline to Week 6 in PANSS total score between brexpiprazole and placebo of −13.5 [95% CI (−23.1, −4.0), p = 0.0057], and those who did not had an LS mean change of −18.9 and a difference between brexpiprazole and placebo of −2.9 [95% CI (−7.2, 1.4), p = 0.1809].Conclusion:Pre-specified sensitivity analyses showed separation from placebo for brexpiprazole at Week 6. A post hoc analysis suggested a potential confounding of efficacy rating towards symptom improvement in patients who experience known side effects of quetiapine XR.

Interactions of antidepressants, mood-stabilisers and antipsychotics with food

Aim: The aim of the paper was to review and analyse the literature addressing interactions between food and antidepressants, mood stabilisers and antipsychotics. Literature review: The observed food and drug interactions are mutual and might lead to a decrease of the therapeutic effect, an increase of the drug toxicity or changes in the nutritional status. Drug and food interactions can modify the pharmacokinetic (e.g. absorption, metabolism) and/or pharmacodynamic properties of drugs. The food intake alters the absorption of trazodone XR, sulpiride, ziprasidone, lurasidone and quetiapine XR. Coffee, tea and possibly turmeric influence CYP1A2 in a dose-dependent manner. Fruit juices (grapefruit, Seville orange, blueberry), curcumin and piperine inhibit CYP3A4. In human studies, significant interactions between food and sertraline, clomipramine, clozapine and carbamazepine were found. Food containing tyramine was shown to interact with MAO inhibitors altering their pharmacodynamic properties. Both malnutrition and obesity may have an impact on the pharmacokinetic properties of some mood stabilisers and antipsychotics. On other hand, the majority of antipsychotics, mood stabilisers and some antidepressants induce weight gain. Changes in taste perception can occur during pharmacotherapy with some antidepressants (tricyclics, selective serotonin reuptake inhibitors), antipsychotics (risperidone) and mood-stabilisers (lithium, valproate). Conclusions: Appropriate care and consideration must be taken when attempting to extrapolate results of in vitro or animal studies to humans. To evaluate the clinical significance of a specific food and drug interaction, it might be necessary to measure the concentration of the pharmaceutical compound and its metabolites in blood serum.